BHS 320 Benchmark Emerging Issues in Brain Technology PDF

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Benchmark – Emerging Issues in Brain Technology

College of Humanities and Social Sciences, Grand Canyon University BHS-320: Ethics of Behavioral Health Science Professor Smith November 14, 2021

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Emerging technology is a term that usually refers to new technology, but it can also refer to the continuous advancement of existing technology. It has slightly various meanings depending on the context such as media, industry, research, or education. There is a wave of new brain technologies on the horizon nowadays. All information in this paper will be based off the writer of this research paper and from two separate resources that will explain the ethical implications, conclusions, and opinions on the future of fNIRS, which will be a new brain technology. As mentioned, the new brain technology fNIRS is known as functional Near-Infrared Spectroscopy. fNIRS is the non-invasive, discrete, compact, and low-cost indirect and direct monitoring of brain activity (Irani et al., 2007). It is a new neuroimaging approach that is more ecologically applicable. It also has the research that can eventually translate lab work into more practical daily and therapeutic settings. According to Naseer and Hong (2015), “The aim is to acquaint clinicians and researchers with the unique and beneficial characteristics of fNIRS by reviewing its relative merits and limitations vis-à-vis other brain-imaging technologies such as functional magnetic resonance imaging (fMRI)”. This technology will help all researchers and medical experts to learn new ways of psychiatric conditions such as schizophrenia and anxiety disorders. Even if fNIRS is a new technology, it still requires some cross validation with more established functional neuroimaging techniques. Even if fNIRS has already been approved by the FDA, all research done with live patients will have ethical questions based on how the data is acquired and how the patients are treated. In the journal of Clinical Neuropsychologist, Irani et al. (2007) are big fans of functional near-infrared spectroscopy. It seems impossible now, but they mention that because of the limits within existing functional neuroimaging technologies, the use of fNIRS enables the development

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of ecologically valid translational research and clinical trials. They also mention that it still has many limitations that include “limited spatial resolution, use of cranial reference points, attenuation of the light signal by extracerebral matter, comparisons of fNIRS data between subjects, the impact of skin pigmentation on signal detection, difficulties obtaining absolute baseline concentrations of oxy-Hb and deoxy-Hb, failures to replicate, high signal-to-noise ratios in EROS signals, its early developmental stage, and the need for informatics-driven modifications of clinical databases based on standardized and normative data” (Irani et al., 2007). An easier way to say this, despite the current limitations on it, fNIRS is an FDA approved novel brain technology that can offer considerable advantages compared to other current techniques such as PET scans or MRI scans. According to the writer of this research paper, this technology will be extremely valuable in the future. Similar technologies, such as PET scans and MRI scans, are greatly used and offer medical practitioners with a lot of information. If the information in this Clinical Neuropsychologist article is right, fNIRS has more advantages as it costs less and is less invasive than other technologies (Irani et al., 2007). fNIRS, according to the writer of this research paper, will be valuable for patients who are unable to receive other types of imaging, such as newborns and children. fNIRS is an exciting new technology that will help doctors better comprehend brain and behavioral problems.

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References Irani, F., Platek, S. M., Bunce, S., Ruocco, A. C., & Chute, D. (2007). Functional near infrared spectroscopy (fNIRS): An emerging neuroimaging technology with important applications for the study of brain disorders. CLINICAL NEUROPSYCHOLOGIST, 21(1), 9–37. Retrieved from https://doi-org.lopes.idm.oclc.org/10.1080/13854040600910018 Naseer, N., & Hong, K.S. (2015). fNIRS-based brain-computer interfaces: a review. Frontiers in Human Neuroscience, 9. Retrieved from https://doiorg.lopes.idm.oclc.org/10.3389/fnhum.2015.00003...